Method for providing a 3D image data record with suppressed aliasing artifacts overlapping the field of view and computed tomograph

ABSTRACT

A method is provided for providing a 3D image data record relating to a biological object with suppressed aliasing artifacts overlapping the field of view caused by an incomplete geometric capture of the object by a computed tomography. A first 3D image data record is provided to describe a subarea of the object. A second 3D image data record is obtained by the computed tomography including data relating to the subarea of the object and is registered with the first 3D image data record. Data of the second 3D image data record is extended and/or amended according to data of the first 3D image data record. A part of such data of the second 3D image data record can be assigned to an aliasing artifact overlapping the field of view and thus generates a modified second 3D image data record with suppressed aliasing artifacts overlapping the field of view.

CROSS REFERENCE TO RELATED APPLICATION

This application claims priority of German application No. 10 2011 075917.4 filed May 16, 2011, which is incorporated by reference herein inits entirety.

FIELD OF INVENTION

The invention relates to a method for providing a 3D image data recordrelating to a biological object with suppressed aliasing artifactsoverlapping the field of view, which are caused by an incompletegeometric capture of the biological object by means of a computedtomograph. The invention also relates to a computed tomograph having anx-ray source, a detector and an image evaluation apparatus, which isembodied to execute such a method.

BACKGROUND OF INVENTION

The x-ray and/or tomography images obtained by x-ray image recordingapparatuses, in particular computed tomographs, may comprise variousimage artifacts. One type of image artifact is used such that themeasured object is not completely captured during the measuring processin terms of its geometric extension. Part of the object undermeasurement is positioned outside of the field of view and is in thismanner truncated, so to speak, in respect of the image obtainedtherefrom. The image artifacts resulting herefrom can be referred tobelow as aliasing artifacts overlapping the field of view. They play anessential role particularly in computed tomographs, since athree-dimensional image obtained by means of back projection isfrequently based on a plurality of projection images, not all of whichcapture the object to be measured wholly or completely. The object isnot constantly completely within the field of view, namely during themeasuring process.

This unwanted data shortening may be meaningful in the case of allcomputed tomographical scan apparatuses, but nevertheless plays asignificant roll particularly with flat panel computed tomographs (see“W. A. Kalender and Y. Kyriaku. Flat-detector CT. Eur Radiol.(11):2767-79, 2007”). With flat panel detector computed tomographs, theview field and/or field of view of the detector which can be capturedduring the measurement only amounts to approximately 20-25 cm in termsof diameter. This restriction makes the prevention of aliasing artifactsoverlapping the field of view almost impossible. Aliasing artifactsoverlapping the field of view significantly impair the quality of aresulting x-ray and/or tomography image. The artifacts not only herewithappear in the vicinity of the image edge, but instead also influencecentral areas of the recorded image.

Aliasing artifacts overlapping the field of view would then not occurfor instance if the x-ray radiation was not attenuated at all borderareas of the field of view. A defined transition in respect of theabsorption values to zero then results. If this transition is howevernot correctly given, this results during the computed tomographyrecordings particularly after filtered back projection (see for instance“A. C. Kak and M. Slaney. Principles of Computerized TomographicImaging. IEEE Press, 1988”, “L. A. Feldkamp, L. C. Davis, and J. W.Kress. Practical cone-beam algorithm. J. Opt. Soc. Am. A, 1(6):612-619,1984”) in the effect that aliasing artifacts overlapping the field ofview appear and an apparent increase in the x-ray radiation attenuationvalues to the image borders is observed. A pale white ring appears inthe computed tomography image beyond the border of the field of view.Strip-like artifacts also result outside of the actual field of viewarea.

Aliasing artifacts overlapping the field of view are generallysuppressed such that image areas at the edge of the field of view, towhich attenuation values greater than zero are assigned, areextrapolated such that a smoothed value curve is produced toward thex-ray absorption value zero. According to a known method, the truncationareas are extrapolated in the computed tomography projection images usedfor the back projection onto an attenuation value of zero and it is onlythen that the filtered back projection is implemented. Within the scopeof this extrapolation method, objects are approached for instance bymeans of a water cylinder (see “Hsieh J, Chao E, Thibault J, GrekowiczB, Horst A, McOlash S and Myers T J, 2004, A novel reconstructionalgorithm to extend the CT scan field-of-view Med. Phys. 31, 2385-91”).The patient as a whole can also be approximated as a water ellipsoid, sothat in this manner data exists for the extrapolation (see “Maltz J S,Bose S, Shukla H P and Bani-Hashemi A R, 2007, CT truncation artifactremoval using water-equivalent thicknesses derived from truncatedprojection data Proc. IEEE Eng. Med. Biol., Soc. 2007. 2907-11”). Asquare extrapolation is for instance known from “Sourbelle K, KachelrieBM and Kalender W A, 2005, Reconstruction from truncated projections inCT using adaptive detruncation Eur. Radiol. 15, 1008-14”, while aso-called sinogram interpolation is described in “Zamyatin A A andNakanishi S, 2007, Extension of the reconstruction field of view andtruncation correction using sinogram decomposition Med. Phys. 34,1593-604”. Further extrapolation methods are known from the followingpublications: “Janoop K P and Rajgopal K, 2007, Estimation of missingdata using windowed linear prediction in laterally truncated projectionsin cone-beam CT Proc. IEEE Eng. Med. Biol. Soc. 2007, 2903-6”, “StarmanJ, Pelc N, Strobe N and Fahrig R, 2005, Estimating 0^(th) and 1^(st)moments in C-arm CT data for extrapolating truncated projections Proc.SPIE 5747, 378-87” and “Sourbelle K, KachelrieB M and Kalender W A,2005, Reconstruction from truncated projections in CT using adaptivedetruncation Eur. Radiol. 15, 1008-14”.

The methods known from the prior art have the objective of improving theimage quality within the field of view area, but nevertheless impairingan image modification or quality improvement outside of the field ofview area. In the event that several border areas are truncated in thecomputed tomography projection images, further serious disadvantagesresult. With the majority of methods, at least one non-truncatedprojection image is needed in order to ensure the fulfillment of aconsistency criterion. A conversion from 3D into 2D data is frequentlyextremely time-consuming. Extremely shortened data records, such as arethe rule with flat panel computed tomographs, cannot be overcome by theusual methods with respect to the aliasing artifacts overlapping thefield of view. In addition, anatomical information is frequently lost.The contour of a patient is generally not correctly reproduced, whichhampers a treating physician during an operation for instance, whennavigating instruments in the body of the patient with the aid of thecomputed tomography image.

SUMMARY OF INVENTION

It is the object of the invention to provide a method and an x-ray imagerecording apparatus with which aliasing artifacts overlapping the fieldof view can still be better suppressed.

This object is achieved by a method and a computed tomography whichcomprise the features of the claims.

The inventive method is used to provide a 3D data record relating to abiological object with suppressed aliasing artifacts overlapping thefield of view, which are caused by an incomplete geometric detection ofthe biological object by means of a computed tomograph. It includes thefollowing steps:

-   a) providing at least one first 3D image data record to describe at    least one subarea of the biological object;-   b) obtaining a second 3D image data record with respect to the    biological object by means of a computed tomograph,    -   wherein the second 3D image data record includes data relating        to the at least one subarea of the biological object described        by the first 3D image data record;-   c) registering the first 3D image data record with the second 3D    image data record;-   d) extending and/or amending the second 3D image data record as a    function of data of the first 3D image data record for at least one    part of such data of the second 3D image data record, which can be    assigned to an aliasing artifact overlapping the field of view and    thus generating a modified second 3D image data record with    suppressed aliasing artifacts overlapping the field of view.

If the second 3D image data record obtained on the biological object isto be incomplete with respect to the geometric capture of the biologicalobject, this is in particular a cause of aliasing artifacts overlappingthe field of view occurring in the resulting computed tomography images.By providing the at least one first 3D image data record, incompletedata can then in particular be extended in the second 3D image datarecord such that the aliasing artifacts overlapping the field of vieware suppressed or even completely prevented. By means of the first 3Dimage data record, the appearance of aliasing artifacts overlapping thefield of view is already prevented so that if necessary, a subsequentmodification and/or processing of a resulting computed tomography imagecan be omitted with respect to the retouching of aliasing artifactsoverlapping the field of view. The method therefore does not suppressaliasing artifacts overlapping the field of view by processing the imageof a resulting image but instead assesses in advance, by extending thedata structure underlying the image so that the artifacts do not appearin the first place. The provision of a concrete first 3D image datarecord dispenses with imprecise and rough assumptions for themodification of the second 3D image data record. A qualitativelyimproved and modified second 3D image data record is thus available,from which meaningful computed tomography images can be obtained.Aliasing artifacts overlapping the field of view are prevented veryefficiently. Assessing the resulting computed tomography images is thuseasier for a person.

Provision can be made in particular for several 3D image data records tobe obtained for instance by means of the computed tomograph in order todescribe several projection images of the biological object and then thesecond 3D image data record is obtained with the aid of these 2D imagedata records by means of back projection. In particular, provision canbe made for the first 3D image data record to provide an image model ofthe biological object. Registration is in particular understood to meanthe image registration of the first 3D image data record with the second3D image data record. This may in particular result in the assignment ofthe first and second 3D image data record which is correct in terms ofposition and/or form, for instance by way of a suitable coordinatetransformation. The extension and/or amending of the data of the second3D image data record can either take place directly by means of the dataof the first 3D image data record or new data can however be obtained onthe basis of the data of the first 3D image data record, with the aid ofwhich the data of the second 3D image data record is extended and/oramended. Data of the second 3D image data record, which can be assignedto an aliasing artifact overlapping the field of view, may in particularbe such data which can be assigned to a border area of the image, whichis described by the 3D image data record.

The method preferably includes the further step of obtaining a 2D imagedata record from the modified second 3D image data record and herefrom acomputed tomography image, in particular a forward projection imageand/or an x-ray sectional image is generated. Forward projection imagesand x-ray sectional images allow a meaningful interpretation of themeasuring data by means of an operating person. Since, within the scopeof the method, aliasing artifacts overlapping the field of view in such2D images are prevented particularly effectively, a very realistic imageof the actual characteristics of the measuring object is obtained.

Step c) preferably includes the following sub-steps:

-   c1) assigning data of the first 3D image data record to data of the    second 3D image data record in a fashion which is correct in terms    of position and dimension;-   c2) determining a comparison value, which is a measure of the degree    of the match between the data assigned to one another in step c1).    The comparison value can be in particular a similarity value in    respect of an image comparison of the image assigned to the first 3D    image data record and of the image assigned to the second 3D image    data record. In order to determine the similarity of two images,    methods known from the prior art can be used;-   c3) modifying the data of the first 3D image data record assigned to    the second 3D image data record in step c1) such that the comparison    value changes compared with the comparison value determined in step    c2) such that the degree of matching increases, particularly by    amending the first 3D image data record with the aid of draw points.    Provision can in particular be made for the first 3D image data    record to be modified such that it compares at least a sub-quantity    of the second 3D image data record in respect of its image    similarity. This can take place for instance in particular pixel by    pixel or voxel by voxel, wherein the gray-scale value deviation in    the two image data records can be used as a comparison value. Images    of an object with a specific contour can be assigned in particular    to the 3D image data records, wherein this contour can be provided    with draw points at specific points. Provision can then be made for    the contour of the image described by the first 3D image data record    preferably to be changeable in terms of image in the vicinity of the    draw points. Draw points may in particular be understood to mean    anchor points in a vector-graphical representation of the image    assigned to the first 3D image data record;-   c4) preferably repeating steps c1) to c3).

The approximation of the first 3D image data record to the second 3Dimage data record preferably therefore takes place iteratively. In thisway, deviations in respect of the shape and design of a mirroring imageobject in the first 3D image data record can be adjusted such that theimage registration in the second 3D image data record is optimized. Theextension and/or amendment of the second 3D image data record then takeplace in an even more realistic fashion.

The first 3D image data record provided in step a) is preferablyobtained with the following sub-steps:

-   -   Providing at least two image data records relating to at least        two comparison objects, which are embodied in a similar or        identical fashion to the object.    -   Determining the first 3D data record in order to describe the at        least one subarea of the biological object by obtaining an        averaged effective image data record from the at least two image        data records.

Biological objects of the same type (e.g. hand, hip, etc.) usuallyindicate variations from living being to living being. It is thereforeadvantageous to provide an averaged image of the biological object inorder to be able to amend or extend the second 3D image data record in avery universal fashion. Faults in the visual description of thebiological object are kept to a minimum. The first 3D image data recordmay then be assigned in particular to a statistical shape model of ananatomical structure.

The at least two image data records of the at least two comparisonobjects are then preferably created with the aid of computed tomographyimages of real comparison objects, wherein a segmentation of thecomputed tomography images is implemented in the creation step. Realcomparison objects may in particular be real body parts of livingbeings, from which image data is obtained. This image data can then beprocessed such that an average image is generated from the individualimages which then forms the basis of the first image data record. Afirst 3D image data record is herewith created, which reproduces thereal situation very well. Alternatively, provision can however also bemade for the first 3D image data record to be obtained with the aid ofan image simulation method, e.g. a method of constructive solid bodygeometry (e.g. CAD). Computed tomography and/or magnetic resonance datamay form the basis of the first 3D image data record.

A database with at least two different 3D image data records ispreferably provided in step a), which describe different subareas of abiological object or different biological objects. For instance, thedatabase may include different 3D image data records relating todifferent body parts. The image registration can then take place suchthat the most suitable 3D image data record is selected from the 3Dimage data records available in the database, i.e. that image datarecord which features the greatest similarity to an image object in thesecond 3D image data record. Provision can however also be made for themost suitable 3D image data record to be manually selected for instanceby means of an operating person. It is then ensured that the second 3Dimage data record is only extended and/or amended by such data whichalso corresponds to the actually existing real situation.

First data is preferably selected in the at least one first 3D imagedata record provided, in particular by way of a binary segmentation,which can be assigned to a specific biological tissue type of thebiological object and in which obtained second 3D image data record,second data is selected, in particular by way of a binary segmentation,which can be assigned to the same biological tissue type. In step c),the image registration preferably then takes place with the aid of thefirst and second data. For instance, provision can be made for the firstand second data to be selected such that it corresponds to bone materialof the biological object if the biological object includes bone materialand soft tissue. Then, in step c), the image registration can beimplemented in two stages, wherein in a first stage, an imageregistration takes place with the aid of the first and second dataassigned to the bone material and in a second stage downstream of thefirst stage, a refined image registration takes place with the aid ofthe data of the first and second image data record, which are assignedto the soft tissue. A particularly precise and reliable imageregistration is ensured in this way, thereby rendering possible acorrect extension and amendment of the data of the second 3D image datarecord.

An inventive computed tomograph includes an x-ray source, a detector andan image evaluation apparatus, which is embodied to execute theinventive method. The computed tomograph may in particular include anx-ray C-arm and be embodied as a PET/CT system. Provision can inparticular also be made for the detector to be embodied as a flat paneldetector. The method is then particularly effective for suppressing thealiasing artifacts overlapping the field of view.

The preferred embodiments represented with reference to the inventivemethod and their advantages apply accordingly to the inventive computedtomographs.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention is explained in more detail below with reference toexemplary embodiments, in which:

FIG. 1 shows a schematic representation of an x-ray C-arm computedtomograph; and

FIG. 2 shows a schematic illustration of an exemplary embodiment of theinventive method.

DETAILED DESCRIPTION OF INVENTION

Identical or functionally identical elements are provided with the samereference characters in the figures.

FIG. 1 shows a computed tomograph 10 with an x-ray C-arm 18, to one endof which an x-ray source 12 is fastened which emits x-ray radiation S inthe direction of an x-ray detector 14. A patient 16 is arranged on acouch between the x-ray source 12 and the x-ray detector 14, wherein abody part of the patient is irradiated by the x-ray radiation S.

The x-ray C-arm 18 is embodied to be rotatable and can in this waydetect the body part of the patient 16 from different perspectives or atdifferent angles. In this way, different x-ray projection images can bedetected by way of the x-ray detector 14, which are transferred by wayof a computer 20. A 3D image data record 28 can be reconstructed fromthe projection images by way of a method for back projection. The 3Dimage data record 28 of the body part is shown schematically in FIG. 2.In the exemplary embodiment, the body part is an arm 22 of the patient16. The arm 22 is only detected in one subarea 32 and thus incompletelyon account of the restricted view field of the x-ray source 12 and x-raydetector 14. In the exemplary embodiment, the hand is almost partiallytruncated. The capture area S1 does not cover the arm 22 completely. Ifa 3D image is generated from the 3D image data record 28, e.g. by meansof forward projection, this indicates aliasing artifacts overlapping thefield of view or truncation artifacts on account of the truncated hand.

A method is therefore proposed, with the aid of which missinginformation in the defective 3D image data record 28 can be extended.Statistical shape models of anatomical structures are used here. Such amodel is formed by a 3D master image 26 of the arm 22. The 3D masterimage 26 covers a larger subarea 34 of the arm 22 than the 3D image datarecord 28. Such a statistical shape model may be generated on the arm 22(or on a hip or a shoulder region for instance) such that informationfrom various recorded and segmented computed tomography data records areused. Provision is made for the 3D master image 26 to exist in adatabase 24 in the computer 20. Different computed tomography datarecords of the respective anatomical regions may exist here.

Within the scope of a binary segmentation, bones and soft tissuematerial are initially separated from one another. The result of thissegmentation provides data records, which minor surface forms and arestored in the database. Different methods can be used to generate thesurface, like for instance thin plate splines or surface morphing.

A similar segmentation to the 3D master image 26 is also implemented onthe 3D image data record 28. Image areas, which can be assigned to bonematerial, can in this way similarly be distinguished from image areaswhich correspond to the soft tissue.

A 3D-3D image registration then takes place automatically or manuallybetween the 3D image data record 28 and the 3D master image 26. Theimage areas, which correspond to the bone material, are used here as afirst match criterion for the image registration. An adjustment by meansof the image areas, which correspond to the soft tissue, can take placein a second step within the scope of a refined image registration. Thisimage registration takes place in step R.

Within the scope of this image registration, the 3D master image 26stored in the database 24 can be adjusted to the subarea 32 in the 3Dimage data record 32 within the scope of a deformation method (e.g.thin-plates spline-warping) such that a good match is achieved.

A modified 3D image data record is produced, in which the original areaS1 of the 3D image data record 28 is extended to an area S2 on accountof the additional information of the 3D master image 26. The subarea 32of the 3D image data record 28 is herewith extended by the extensionarea 36, which results from the subarea 34 of the 3D master image. As aresult, the modified 3D image data record 30 is achieved.

The thus resulting modified 3D image data record 30 can now be projectedforwards so that a projection image results in which the aliasingartifacts overlapping the field of view are suppressed. The thusobtained computed tomography image can also be smoothed by way of ahistogram analysis, so that the image quality is improved.

The presented method is advantageous in that very defective or noisyx-ray image data can be significantly improved in respect of theirquality by the statistic shape model. The 3D master image 26 providesanatomically correct data, by means of which a very preciseextrapolation of the 3D image data record 28 is possible. Extrapolationmethods known from the prior art must instead be based here on waterellipsoids for instance, since no anatomical information exists in thetruncation area. The shape and design of the patient can now beprecisely considered. Additional sensors are not necessary.

The invention claimed is:
 1. A method for providing a 3D image datarecord of a biological object with a suppressed aliasing artifactoverlapping a field of view, wherein an aliasing artifact overlappingthe field of view is caused by an incomplete geometric capture of thebiological object by a computed tomograph, comprising: providing a first3D image data record describing a subarea of the biological object;obtaining a second 3D image data record of the biological object by thecomputed tomograph, wherein the second 3D image data record includesdata relating to the subarea of the biological object described by thefirst 3D image data record; registering the first 3D image data recordwith the second 3D image data record; extending and/or amending data ofthe second 3D image data record as a function of data of the first 3Dimage data record so that a part of the data of the second 3D image datarecord can be assigned to the aliasing artifact overlapping the field ofview; and generating a modified second 3D image data record with thesuppressed aliasing artifact overlapping the field of view, wherein thefirst 3D image data record is registered with the second 3D image datarecord by: positionally and dimensionally assigning the data of thefirst 3D image data record to the data of the second 3D image datarecord; determining a degree of match between the data assigned to oneanother; and modifying the data of the first 3D image data recordassigned to the data of the second 3D image data record by draw pointsso that the degree of match increases.
 2. The method as claimed in claim1, further comprising: obtaining a 2D image data record from themodified second 3D image data record, and generating a forwardprojection image and/or an x-ray sectional image from the 2D image datarecord.
 3. The method as claimed in claim 1, wherein the first 3D imagedata record is provided by: providing at least two image data recordsrelating to at least two comparison objects which are similar oridentical to the biological object; and determining the first 3D imagedata record describing the subarea of the biological object by obtainingan averaged effective image data record from the at least two image datarecords.
 4. The method as claimed in claim 3, wherein the at least twoimage data records of the at least two comparison objects are created bycomputed tomography images, and wherein the computed tomography imagesare segmented.
 5. The method as claimed in claim 1, wherein the first 3Dimage data record is stored in a database, and wherein the databasecomprises at least two different 3D image data records describingdifferent subareas of the biological object or different biologicalobjects.
 6. The method as claimed in claim 1, wherein a first data isselected in the first 3D image data record by a binary segmentation andis assigned to a specific type of biological tissue of the biologicalobject, wherein a second data is selected in the second 3D image datarecord by a binary segmentation and is assigned to a same type of thebiological tissue of the biological object, and wherein the first 3Dimage data record is registered with the second 3D image data recordaccording to the first and the second data.
 7. A computed tomography,comprising: an x-ray source; an x-ray detector; and an image evaluationapparatus adapted to execute a method comprising the steps of: providinga first 3D image data record describing a subarea of the biologicalobject; obtaining a second 3D image data record of the biological objectby the computed tomograph, wherein the second 3D image data recordincludes data relating to the subarea of the biological object describedby the first 3D image data record; registering the first 3D image datarecord with the second 3D image data record; extending and/or amendingdata of the second 3D image data record as a function of data of thefirst 3D image data record so that a part of the data of the second 3Dimage data record can be assigned to the aliasing artifact overlappingthe field of view; and generating a modified second 3D image data recordwith the suppressed aliasing artifact overlapping the field of view,wherein the first 3D image data record is registered with the second 3Dimage data record by: positionally and dimensionally assigning the dataof the first 3D image data record to the data of the second 3D imagedata record; determining a degree of match between the data assigned toone another; and modifying the data of the first 3D image data recordassigned to the data of the second 3D image data record by draw pointsso that the degree of match increases.
 8. The computed tomograph asclaimed in claim 7, wherein the x-ray detector is a flat panel detector.